Forensic integrity of blood alcohol sampling in the emergency department, Part II: Establishing quality goals of turnaround time with Monte Carlo simulation.
{"title":"Forensic integrity of blood alcohol sampling in the emergency department, Part II: Establishing quality goals of turnaround time with Monte Carlo simulation.","authors":"Cristiano Ialongo","doi":"10.11613/BM.2026.030704","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>In the emergency department (ED), the turnaround time (TAT) for forensic blood alcohol sampling is a critical determinant of legal admissibility. Due to the pharmacokinetics of ethanol, delays in sampling lead to metabolic decay, potentially resulting in pharmacokinetic false negatives (FN<sub>pk</sub>). This study aims to establish objective, evidence-based quality goals for intra-ED TAT using Monte Carlo simulation to preserve forensic reliability.</p><p><strong>Materials and methods: </strong>Data were collected from 121 forensic cases at a major metropolitan university hospital in 2025. A Monte Carlo simulation (N = 50,000 iterations) was performed to model the probability of FN<sub>pk</sub> based on ethanol elimination rate (β), analytical imprecision (CV), and extra-ED <i>versus</i> intra-ED TAT components. Probability density functions (PDFs) were fitted using Weibull and Gamma distributions to characterize observed clinical and logistical data.</p><p><strong>Results: </strong>The simulation revealed a baseline P(FN<sub>pk</sub>) of 7.0% for the intra-ED phase, increasing to 7.6% when including extra-ED transport. Quality goals were derived for three tiers: optimal (TAT<sub>95%</sub>) at 134 minutes, acceptable (TAT<sub>80%</sub>) at 214 minutes, and minimum (TAT<sub>60%</sub>) at 273 minutes. Regression analysis showed that for every 1% increase in assay CV, the TAT quality goal erodes by 2.7 to 3.3 minutes. The logistic process was found efficient, with an Index of Logistic Reliability (I<sub>LR</sub>) of 86.4%.</p><p><strong>Conclusions: </strong>Monte Carlo simulation effectively translates pharmacokinetic variables into actionable forensic quality goals. Current ED performance requires process improvement, particularly in the request-transmission phase, to minimize FN<sub>pk</sub> and ensure forensic equity.</p>","PeriodicalId":94370,"journal":{"name":"Biochemia medica","volume":"36 3","pages":"030704"},"PeriodicalIF":1.8000,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13489493/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biochemia medica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11613/BM.2026.030704","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/8/10 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
Introduction: In the emergency department (ED), the turnaround time (TAT) for forensic blood alcohol sampling is a critical determinant of legal admissibility. Due to the pharmacokinetics of ethanol, delays in sampling lead to metabolic decay, potentially resulting in pharmacokinetic false negatives (FNpk). This study aims to establish objective, evidence-based quality goals for intra-ED TAT using Monte Carlo simulation to preserve forensic reliability.
Materials and methods: Data were collected from 121 forensic cases at a major metropolitan university hospital in 2025. A Monte Carlo simulation (N = 50,000 iterations) was performed to model the probability of FNpk based on ethanol elimination rate (β), analytical imprecision (CV), and extra-ED versus intra-ED TAT components. Probability density functions (PDFs) were fitted using Weibull and Gamma distributions to characterize observed clinical and logistical data.
Results: The simulation revealed a baseline P(FNpk) of 7.0% for the intra-ED phase, increasing to 7.6% when including extra-ED transport. Quality goals were derived for three tiers: optimal (TAT95%) at 134 minutes, acceptable (TAT80%) at 214 minutes, and minimum (TAT60%) at 273 minutes. Regression analysis showed that for every 1% increase in assay CV, the TAT quality goal erodes by 2.7 to 3.3 minutes. The logistic process was found efficient, with an Index of Logistic Reliability (ILR) of 86.4%.
Conclusions: Monte Carlo simulation effectively translates pharmacokinetic variables into actionable forensic quality goals. Current ED performance requires process improvement, particularly in the request-transmission phase, to minimize FNpk and ensure forensic equity.